import numpy as np


namelist = np.array(['最大值','最小值','四个相邻像素二阶差的绝对值之和。使用对角拉普拉斯滤波器计算二阶差分，','四个相邻像素值之间的差值之和','复杂度','四个相邻像素值之间差异的方差','像素点和周边12个像素的的差值和','其相邻像素左侧梯度的大小之和','其相邻像素右侧梯度的大小之和','四个相邻像素左梯度之间差异的大小之和','四个相邻像素右梯度之间差异的大小之和','sobel mask','0，45，90，135度角','周边四个像素方差','以xn，m为中心的四个水平像素的局部方差计算','以xn，m为中心的四个竖直像素的局部方差计算','表示以xn，m为中心的5×5尺寸块的水平差和垂直差之和','12个点像素和其均值求差然后求和','45度梯度大小之和','由本地二进制模式（LBP）提取'])
# a = np.array([ 93, 139,  93, 139, 255, 209,  23,  23,  70, 139,  46,   0,   0,  23,  23,   0, 116,   0,   0,  23])
# b = np.argsort(-a)
datakey = np.array([10, 4, 7, 2, 1])
c =namelist[datakey]
print(c)
# for j in range(10,200):
#     c = bin(j)
#     # d =
#     c = ''.join(c[2:])
#     d = []
#     d.__iadd__(c)
#     d = np.array(d, dtype=int)
#     chooselist = np.zeros(10)
#     chooselist[10 - len(d):] = d
#     totalsize = int(np.sum(chooselist))
#     rows = chooselist.shape[0]
#     chooselist = chooselist.reshape((rows, -1))
#     a = np.random.random((10,20))
#     b = a*chooselist
#     list=[]
#     for i in range(len(chooselist)):
#     #     print(chooselist[i])
#         if chooselist[i] == 0:
#             list.append(i)
#     list = np.array(list)
#     f = np.delete(b, list, 0)
#     print(f.shape)